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Record W2153851620 · doi:10.1177/0306624x14533109

An Examination of Escalation in Burglaries Committed by Sexual Offenders

2014· article· en· W2153851620 on OpenAlexaff
Amélie Pedneault, Danielle Arlanda Harris, Raymond A. Knight

Bibliographic record

VenueInternational Journal of Offender Therapy and Comparative Criminology · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCrime Patterns and Interventions
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPsychologyCriminologySexual violenceAggressionSex offenseCommissionPoison controlHuman factors and ergonomicsSocial psychologyMedical emergencyPolitical scienceSexual abuseLawMedicine

Abstract

fetched live from OpenAlex

Research in the field of sexual aggression often assumes escalation in the criminal careers of sexual offenders. Sexual offenders are thought to begin their criminal careers with non-contact sexual offenses or non-sexual offenses and then escalate to more serious crimes, specifically sexual violence. The commission of one crime in particular--burglary--has been found to be a predictor of future violence in sexual offenders. The present study investigated the nature and extent of escalation in the criminal histories of 161 sex offenders who committed at least two burglaries. Six types of escalations were considered: type of burglary, occupancy, violence, weapon, frequency, and the victim-offender relationship. Escalators and non-escalators were compared, differences between the groups were reviewed, and the cumulative effect of various forms of escalation was analyzed. Results indicated that escalators and non-escalators could be differentiated on a number of important dimensions that might assist in the earlier detection of subsequently more dangerous offenders.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.785
Threshold uncertainty score0.301

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.279
GPT teacher head0.406
Teacher spread0.127 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2014
Admission routes1
Has abstractyes

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